[1]} proposed a multi-hop QA dataset (WikiHop) where the answer can only be found using more than one document. Several neural models have been proposed [2]}, [3]}, [4]}, [5]} to solve this task. We have created a two-hop relation extraction dataset (THRED) from this WikiHop dataset. The major difference between these two datasets is that THRED contains many None relations, whereas in the WikiHop dataset, every instance has a correct answer. Extracting the None relation is challenging, since None occurs when no relations in \(R\)  exist. When the number of relations in \(R\)  increases, it becomes more difficult to predict the relations. As such, we believe the multi-hop RE task is more challenging than the multi-hop QA task.
